Evidence map›Paper›PMID 42618713›Full record

Articlenpj health systems2026

Modeling the impacts of budget reductions at the U.S. NIH on research and innovation.

Zeynep Hasgul, Hannah Lee, Mohammad S Jalali

Abstract read
In one paragraph

Article in npj health systems, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Zeynep HasgulCenter for Health Technology Assessment, Mass General Brigham, Harvard Medical School, Boston, MA, USA.
Hannah LeeCenter for Health Technology Assessment, Mass General Brigham, Harvard Medical School, Boston, MA, USA.
Mohammad S JalaliCenter for Health Technology Assessment, Mass General Brigham, Harvard Medical School, Boston, MA, USA. msjalali@mgh.harvard.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Stable public funding underpins biomedical innovation, yet the U.S. research system remains vulnerable to swings in federal budgets. We developed BRIDGE (Biomedical Research Investment Dynamics and Growth Evaluation), a simulation model linking NIH funding to new drug approvals, workforce dynamics, and scientific output. Using 47 longitudinal data measures from 1995-2024, validated against historical trends and projecting outcomes through 2050, we examined multiple funding trajectories, including stable growth, flat budgets, large reductions, and later restorations. Results show that across scenarios, even temporary disruptions create lasting setbacks for drug development, researcher training, and basic science. Later funding increases cannot repair the damage for decades, with persistent losses in capacity and output that highlight how fragile the system is to short-term shocks and why stable public investment is essential for long-term innovation. For example, if the NIH budget were cut by 40% in 2026, even doubling that reduced budget at the start of the next administration would still require 36 years to recover the cumulative loss in novel drug approvals.

Identifiers

PMID42618713
PMCPMC13490408

What OpenQuestion holds

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LicenceCC BY-NC-ND
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.